Amazon Opens Old Wounds for Retailers (Again)

Before we completely move on from last month’s Amazon Prime Day, it’s important to understand why retail brands once again braced themselves to lose customers and online sales when they had a whole year to do things differently. 
 
Amazon’s ingredients for the promotion were extensive and strategic, but were also simple extensions of its carefully built ecosystem: They offered sneak previews of the sale a week in advance, gave Alexa shoppers a several-day head start on Alexa-specific product deals, gave Prime Now members a two-day head start on deals for products with a 2-hour delivery, pushed voice shopping by giving first-time voice shoppers first dibs on deals the day of the promotion, and extended access to 100 Alexa-related deals beyond the close of the promotion.
 
The most glaring takeaway from all of this is that Amazon didn’t do anything that other retailers can’t do themselves. When you break it down, they put together a promotion that rewarded loyal shoppers, drew attention to the benefits of membership, pushed valuable behaviors they want to see more of, and created deal segments according to user and product type. 
 
While there are admittedly few retailers that have the infrastructure and product variety that Amazon does, what most retailers do have is lots and lots of data. And as of very recently, they also have access to advanced technologies like artificial intelligence that can put this data to work so they’re less vulnerable to retailers like Amazon.
 
What continues to stand between many retailers and Amazon is their inability to put technology and data to work for them, so they can think less about the day-to-day minutiae and more about the customer experience. Here’s how Amazon did that and what retailers can learn.
 
Get out of the weeds and put the customer first.
A major inefficiency for retailers is the overwhelming amount of customer data they must wade through to come up with the type of tangible insights — recurring visitor trends, buying patterns, and product preferences — that Amazon bases most of its marketing and promotions on. The same data that allows retailers to hyper target their audiences with personalized messages has simultaneously become way too much for them to analyze and act on creatively in other ways that would enhance the customer experience.
 
Amazon got ahead of this problem years ago by introducing a proprietary technology infrastructure that relies on artificial intelligence and machine learning to maximize customers’ experiences on the site. Because Amazon has automated many of the day-to-day processes that fuel their understanding of their customers, while other retailers still rely on teams to manually crunch and interpret data, Amazon has freed up its teams to work on more creative programs. 
 
Retailer agnostic AI platforms are now emerging to let retailers bridge the gap between themselves and major retailers like Amazon. Amazon Prime Day is a perfect example of what’s possible when retailers have the luxury of time
 
Stop telling customers who they are and what they want.
If the groups that Amazon prioritized for Prime Day taught us anything, it’s that Amazon isn’t overthinking things. In fact, quite the opposite. What Amazon continues to do so well is use its data to identify and understand it customers, both individually and as parts of the larger behavior-driven groups they fall into. Amazon doesn’t make the mistake of pre-determining user segments and buyer personas, and then retroactively fitting customers into them. 
 
Instead, Amazon lets its customers’ demographic and behavioral data tell them what they like and don’t like, what products are trending among which types of people, and where there are both predictable and unexpected patterns that inform larger user trends. Amazon additionally offers its customers several opportunities to self-identify themselves, their commitment level, and their priorities through structured programs like Amazon Prime and Prime Now. All of this gives Amazon digestible groups-based insights that they can use to seamlessly cater to these groups. 
 
Supplement retargeting with rewarding.
Retailers can dedicate a lot of time and resources to retargeting disinterested customers while inadvertently ignoring highly valuable customers they don’t know about. Amazon has solved for this with laser-precision targeting, based on the type of acute insights discussed above. 
 
What they do next is also worth noting. During Amazon Prime Day, Amazon isolated a very specific group of customers to activate: Alexa customers who have not yet used the voice shopping feature. Presumably, Amazon has seen increased order frequency or order values from voice shoppers, and sees an opportunity to grow this segment. So, in retargeting them, Amazon didn’t just put Alexa-related products in front of these shoppers; it rewarded everyone in this very specific segment with two hours advanced access to Prime Day deals and a 6-day extension on voice deals across segments. 
 
Not surprisingly, Amazon reported that "Prime members’ most popular purchase was the Echo Dot, which was not only the best-selling Amazon device this Prime Day, but also the best-selling product from any manufacturer in any category across Amazon globally."
 
There are several other takeaways and lessons to be learned from the success of Prime Day, but at the core of all of it, what Amazon continues to do better than other retailers is use technology to free up time and maximize reach, data to point them in the right direction, and good old-fashioned creativity to tailor promotions that get customers to do and buy what they want them to.
 
For retail brands who have never understood why they couldn’t compete with Amazon, emerging AI solutions will illuminate the advantages Amazon has enjoyed, while simultaneously eliminating them.
 

Or Shani is CEO and founder of Albert, a fully autonomous artificial intelligence platform that drives digital sales and marketing campaigns, from start to finish, for some of the world’s leading brands.

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